| Literature DB >> 27833145 |
Jungbin Mok1,2, Nickolay A Krotkov3, Antti Arola4, Omar Torres3, Hiren Jethva3,5, Marcos Andrade6, Gordon Labow3,7, Thomas F Eck3,5, Zhanqing Li1,2,8, Russell R Dickerson1,2, Georgiy L Stenchikov9, Sergey Osipov9, Xinrong Ren1,10.
Abstract
The spectral dependence of light absorption by atmospheric particulate matter has major implications for air quality and climate forcing, but remains uncertain especially in tropical areas with extensive biomass burning. In the September-October 2007 biomass-burning season in Santa Cruz, Bolivia, we studied light absorbing (chromophoric) organic or "brown" carbon (BrC) with surface and space-based remote sensing. We found that BrC has negligible absorption at visible wavelengths, but significant absorption and strong spectral dependence at UV wavelengths. Using the ground-based inversion of column effective imaginary refractive index in the range 305-368 nm, we quantified a strong spectral dependence of absorption by BrC in the UV and diminished ultraviolet B (UV-B) radiation reaching the surface. Reduced UV-B means less erythema, plant damage, and slower photolysis rates. We use a photochemical box model to show that relative to black carbon (BC) alone, the combined optical properties of BrC and BC slow the net rate of production of ozone by up to 18% and lead to reduced concentrations of radicals OH, HO2, and RO2 by up to 17%, 15%, and 14%, respectively. The optical properties of BrC aerosol change in subtle ways the generally adverse effects of smoke from biomass burning.Entities:
Year: 2016 PMID: 27833145 PMCID: PMC5105132 DOI: 10.1038/srep36940
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Distribution of biomass burning and resultant smoke over South America.
(a) Satellite map of monthly mean aerosol absorption optical depth (AAOD = AOD*(1-SSA)) at 388 nm for September 2007 derived using two-channel OMAERUV aerosol algorithm applied to the Ozone Monitoring Instrument (OMI) on board NASA’s Aura satellite. The OMAERUV aerosol dataset is available from NASA’s Goddard Earth Sciences Data and Information Services Center (http://disc.sci.gsfc.nasa.gov/uui/datasets/OMAERUV_V003/summary?keywords=%2522Aura%20OMI%2522#prod-summary). This plot was created using the IDL (Interactive Data Language) software version 7.1.1. The URL link to access the IDL software is http://www.harrisgeospatial.com/ProductsandSolutions/GeospatialProducts/IDL/Language.aspx. (b) MODIS (Moderate Resolution Imaging Spectroradiometer) true-color image captured on 9 September 2007 over the same region showing active fire locations (marked in red) and a thick blanket of smoke stretching from the Amazon to Argentina; the image was obtained from NASA’s Earth Observatory website54. A solid black triangle shows the location of Santa Cruz.
Figure 2Spectral dependence of smoke aerosol absorption parameters derived from ground-based and satellite (OMI) retrievals during the field campaign in Santa Cruz, Bolivia in September-October 2007.
(a) Imaginary part of the column effective refractive index (k), (b) Single scattering albedo (SSA), (c) Aerosol absorption optical depth (AAOD = AOD*(1-SSA)). Retrievals are from UV-MFRSR (blue symbols), Vis–NIR AERONET (red symbols), and satellite OMI UV (green symbols). All retrievals are shown as box-whisker plots. Boxes are the interquartile range (IQR; 25 to 75 percentiles) and whiskers are stretched to the maximum and minimum within 1.5 times the IQR. The circles show the outliers. The solid red line in a shows the theoretically calculated campaign–average k assuming that BC is the only absorbing component. The error bars in b and c for OMI-retrieved SSA and AAOD (±0.03 for SSA and ±30% for AAOD) are shown as thin vertical lines exceed the whisker’s range.
Estimated BrC mass absorption efficiency (MAEBrC).
| Wavelength [nm] | Total AAOD | AAODBC | AAODBrC = AAOD-AAODBC | MAEBrC [m2/g] (min [ |
|---|---|---|---|---|
| 305 | 0.296 | 0.121 | 0.175 | (2.9–16.1) |
| 311 | 0.233 | 0.120 | 0.113 | (1.8–10.4) |
| 317 | 0.255 | 0.117 | 0.138 | (2.3–12.7) |
| 325 | 0.189 | 0.115 | 0.074 | (1.2–6.8) |
| 332 | 0.212 | 0.114 | 0.098 | (1.6–9.0) |
| 368 | 0.156 | 0.102 | 0.054 | (0.9–5.0) |
We estimate MAEBrC in the UV wavelengths (MAEBrC = 0 in the visible wavelengths) using specific AAODBrC divided by BrC column mass density. The maximum and minimum values of MAEBrC are associated with the range of previously measured kBrC26 at 368 nm (see Methods section for details).
Figure 3The inferred spectral dependence of BrC imaginary refractive index (kBrC) in UV (blue circles with 20% error bars).
Black circles show the upper limit for kBrC-368 values derived from African savanna burning samples (10% uncertainty)2. Lower limit of kBrC-368 parameterization (green dashed lines) is based on smoke chamber experiments6 showing low spectral dependence (w = 1.6). The shaded area shows the variability range in our inferred kBrC in the UV wavelengths. We inferred much larger spectral dependence (w ~ 5.4–5.7) in the UV-B than previously reported (~1.6–4) in longer UV and visible wavelengths26.
Figure 4Enhanced BrC absorption causes 20% decrease in the most damaging short wavelength surface UV-B irradiance (305–320 nm)
. Box-whisker plots show the relative difference [%] between our measured surface spectral UV (BC plus BrC absorption) and model (assuming BC only) surface UV: (UVmeas−UVBC)/UVBC × 100%. Red circles show independent model estimates using different LibRadtran (http://www.libradtran.org) RTM for the fixed SZA (45°) and ozone column amounts (272 DU).
Figure 5Modeling the impact of BrC absorption on the rate of tropospheric ozone production.
The vertical profiles show relative differences [%] in photolysis rates for NO2 (JNO2: dotted line) and ozone to O(1D) (JO3: dashed line) due to enhanced BrC UV absorption for different SZAs using a radiative transfer model. We assumed a homogeneously distributed smoke layer below 3 km as measured by space-based lidar. The ozone loss mechanism linked to JO3 is more significantly reduced than the production mechanism linked to JNO2. Input kret values for calculating photolysis rates are described in Supplementary Table S2.